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Full text of "BSTJ 62: 6. July-August 1983: Human Factors and Behavioral Science: Methods for Field Testing New Telephone Services. (Eigen, D.J.)"

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THE BELL SYSTEM TECHNICAL JOURNAL 
Vol. 62, No. 6, July-August 1983 
Printed in U.S.A. 



Human Factors and Behavioral Science: 



Methods for Field Testing New Telephone 
Services 

By D. J. EIGEN* 
(Manuscript received December 29, 1981) 

Telephone services are increasingly complex and diverse, and they require 
more human-machine interaction than ever before. A field test can help 
improve a new service by ensuring that it is easy to use with little chance for 
error. This paper discusses the methodology of field testing. Specially tailored 
telephone service evaluation methods, based on field test experience with the 
Calling Card Service, are presented in detail. 

I. INTRODUCTION 

New telephone services involve more customer-system interaction 
than ever before, and making the use of these services easy and error- 
free is a major goal of their development. Properly designed dialing 
plans, announcements, timings, tones, and instructions increase cus- 
tomer acceptance, minimize customer errors, and promote use of the 
service. The design of new services can be evaluated by coordinated 
studies that include: 

• Analysis of present services, 

• Interviews with customers, 



Bell Laboratories. 



^Copyright 1983, American Telephone & Telegraph Company. Copying in printed form 
for private use is permitted without payment of royalty provided that each reproduction 
is done without alteration and that the Journal reference and copyright notice are 
included on the first page. The title and abstract, but no other portions, of this paper 
may be copied or distributed royalty free by computer-based and other information- 
service systems without further permission. Permission to reproduce or republish any 
other portion of this paper must be obtained from the Editor. 



1591 



• Laboratory studies of proposed protocols for customer-system 
interactions, 

• Field tests of services, and 

• Product follow-up studies. 

Field testing is the largest and most costly step in this coordinated set 
of studies. This paper discusses the methodology of field testing, using 
a field test of the Calling Card Service as an example. 

II. CALLING CARD SERVICE FIELD TEST OVERVIEW 

An analysis of operator-handled credit card service indicated that a 
reasonable proportion of credit card calls could be automated. Inter- 
views with credit-card, bill-to-third-number, and collect customers 
verified their interest in and need for an automated Calling Card 
Service, and laboratory studies provided evidence that customers could 
use the Calling Card Service successfully. 

The Calling Card Service field test was conducted in Milwaukee 
from November 1977, to June 1978. 1,2 Regular telephone credit card 
numbers could be dialed in order to place Calling Card calls from 
about 3000 noncoin phones in the Milwaukee area and from 70 coin 
phones at Milwaukee's airport, two downtown hotels, and a few local 
restaurants. Bright orange placards on the trial coin phones instructed 
customers on how to use their telephone credit card number. In 
addition, operators were trained to assist callers and answer questions. 
(Calls from unequipped stations were handled as usual.) 

To use the trial Calling Card Service, customers first dialed zero 
plus the number they wished to call. Special programs in the Traffic 
Service Position System (TSPS) routed incoming "0+" calls from trial 
stations to a small team of specially trained operators who helped 
simulate Calling Card Service— in actual service no operators are used. 
Besides the TSPS console, these operators had a video display terminal 
linked to a minicomputer (see Fig. 1). 

When a call arrived from a specially equipped station, the trial 
operator notified the minicomputer, which then delivered a tone to 
prompt the customer to dial a Calling Card number. Detectors received 
the dialed digits and sent them to the minicomputer over a data link 
for verification. Calls with valid Calling Card or credit card numbers 
were allowed to proceed and were billed appropriately. 

Depending on the protocol being tested, the minicomputer displayed 
step-by-step instructions on a terminal screen to guide the operator 
in handling each call. For example, to encourage customers to redial 
after making errors, the minicomputer might display the instruction, 
"Please hang up and dial zero plus the number you are calling," which 
was to be read to the customer. By making simple changes in the 
minicomputer program, the operator's treatment of calls could be 

1592 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



AIRPORT 



HOTELS AND 
RESTAURANTS 



BUSINESSES 



RESIDENCES 




TSPS CONSOLE AND 
COMPUTER TERMINAL 







©@ 




— 





MINICOMPUTER DATABASE 



WAUKESHA, 
WISCONSIN TSPS 



Fig. 1— Test setup. 



altered, often without additional training. This flexible arrangement 
allowed easy testing of many different protocols and rapid changes 
among them. 

The minicomputer recorded the time and details of each call. These 
records were analyzed rapidly to determine how the protocol could be 
improved. Throughout the trial, protocols were varied by changing 
announcements, timings, access to operators, error-correction proce- 
dures, and other aspects of the caller interface. In all, 24 variations of 
the protocol were tested at equipped coin phones, 14 at noncoin 
phones. Over 10,000 customers dialed more than 30,000 automated 
Calling Card calls during the trial and more than 5,000 customer 
interviews were obtained. 

III. FIELD TEST ACTIVITIES 
3.1 Field tests 

In a field test such as that for Calling Card Service, a simulation of 
the proposed service is actually offered to a limited, but representative, 
set of customers on a trial basis. In some circumstances, when there 
is sufficient confidence in the form of the service, the actual product 
can be used as a test vehicle. 

The field test can be used to adjust the technical and operational 
aspects of the service. It can be used to determine whether the service 
fits a customer need, and it can also be used to improve estimates of 
willingness to pay. And finally, it can be used to evaluate customer 
performance, satisfaction, and usage in the effort to provide a service 



FIELD TESTING TELEPHONE SERVICES 1593 



that optimizes the customer-system interaction on which new services 

rely. 

The greater the fidelity of the test to the real service situation, the 
greater one's confidence in the final success of the service being tested. 
Field tests provide increased fidelity over more indirect techniques for 
evaluating services. 
3.2 Study plan 

Developing a study plan is the first task in planning a field test. A 
study plan must include the following five steps: 

1. State the objectives of the study and delineate issues to be 
resolved by it. The primary objectives of the evaluation of the human- 
machine aspects of telephone services are to: 

a. Determine if usage, satisfaction, and performance are at accept- 
able levels. 

b. Predict the levels of usage, satisfaction, and performance in the 
final service. 

c. Refine the service to improve usage, satisfaction, and perform- 
ance. 

Many other detailed issues for a particular service may require reso- 
lution. 

2. Determine constraints on study service and resources necessary 
to accomplish the test. Decisions on test methodology necessarily 
involve practical choices. For example, the marketplace often imposes 
serious time constraints on the development, deployment, and evalu- 
ation of a telephone service. 

3. Design and refine the service and the human-machine interfaces 
involved. Some initial human-machine telephone service interface 
must be defined before the evaluation process can be initiated. Con- 
tinued analyses, interviews, and laboratory studies are best used to 
generate and refine the service alternatives prior to the field test itself. 

4. Delineate variables that may influence the results and hypoth- 
esize their interactions. Three categories of variables need to be 
specified for the field test: 

a. Independent variables — those variables that are to be deliberately 
manipulated or held constant. Among the possible variables of 
this type (with some examples) are the following: 

( 1 ) Service protocol — announcements, tones, timings, error-han- 
dling strategies, and digit strings. 

(2) Capabilities of the service — billing, routing, and screening. 

(3) Availability — geographic constraints, time-of-day con- 
straints, and station-type constraints. 

(4) Type of instruction for customers — media and format. 

(5) Marketing effort — promotion. 

(6) Rate — price structure. 

1594 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



b. Dependent variables — those variables whose values are affected 
by changes in the independent variables. Some examples are 
given below. 

(1) Subscription — initial interest and sign -up rate. 

(2) Usage — rate of first and repeated use. 

(3) Acceptance — judged worth and satisfaction. 

(4) Customer performance — speed, error, and abandonment rate. 

c. Parameters — those identifiable variables that are free to vary. 
Among these are: 

(1) A priori condition — predisposition toward service, demo- 
graphic mix of customer population, etc. 

(2) Internal characteristics — the test design or method used, 
intrinsic characteristics of the customer in the test, etc. 

(3) External characteristics — the geographic, environmental, 
and temporal setting of the test. 

These variables are not necessarily mutually exclusive. Some param- 
eters might be fixed or systematically varied, and, thus, be made 
independent variables. 

It helps to have hypotheses about how these variables will interact. 
Figure 2 demonstrates one model of several possible models of the 
relationships among variables for telephone services. A different model 
might assume that instruction may affect acceptance and subscription 
more directly than is shown in Fig. 2. 

5. Define methods for increasing confidence in the results of the 
study. Some of the most important aspects of a good study plan are 
motivated by the need to counteract rival explanations of the results 



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Fig. 2— Variable block model. 

FIELD TESTING TELEPHONE SERVICES 1595 



and, thereby, increase confidence in the validity of the field test as an 
indicator of the success of the service. 3 " 5 Section IV is devoted to this 
component of the study plan. 

3.3 Test development 

After the study is designed, the following tasks must be done. 

1. Define data gathering tools. 

2. Define data analysis techniques. 

3. Define test service delivery vehicle. 

a. Define test service requirements. 

b. Design test service delivery vehicle. 

c. Implement service delivery vehicle (hardware/software devel- 
opment). 

d. Integrate trial system and test. 

4. Acquire and prepare customers. 

5. Acquire and prepare site(s). 

6. Define test operations and procedures for utilizing results. 
Figure 3 is an illustration of the interrelationships among these tasks. 

3.3. 1 Data collection 

The following data collection methods were used in the Calling Card 
Service field trial. 




Fig. 3 — Evaluation development paradigm. 
1596 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



3.3. 1. 1 Interviews/questionnaires. Interviews and questionnaires pro- 
vide measures of attitude, as well as corroborative measures of usage, 
and can be given before, during, and after the field test. In-person, 
face-to-face interviews with customers who had used the Calling Card 
Service provided some of the more compelling evidence of the success 
of the service. The following spontaneous comments illustrate the 
range of such data. 

Example of positive response: 

1. "It's excellent. I compliment the phone company for coming 

through with this. Makes it a lot easier." 
Example of negative response: 
1. "In the past, you dialed Helen (operator) and said, 'I want to talk 

to Joe,' and right off Joe was on the line — it seems you are trying 

a lot of new services to get rid of Helen." 

3.3.1.2 On-line measurements. These measurements are the machine 
recording of customer and system events, such as picking up a receiver 
or placing it back on the switchhook (hanging up), dialing digits, tones 
or announcements, error detection, and call progress states. By re- 
cording, time stamping, and storing these events, the sequence of 
customer-machine interactions can be reconstructed.* 

3.3.1.3 Billing. Billing records routinely provide various data on a 
call, such as calling and called number, call duration, date, time of 
day, class of charge (e.g., collect, DDD, and so forth). 

3.3. 1.4 Observation. Observation provides a crude but valuable tech- 
nique for gathering data that cannot be obtained by other means. 

3.3. 1.5 Customer feedback. Feedback mechanisms for customer com- 
plaints and suggestions are maintained by the telephone companies 
offering the service. 

3.3.1.6 Records. Records and logs of equipment malfunction and 
events recorded in newspapers are important for detecting or counter- 
acting erroneous or misleading results. Data in such records can be 
used to measure dependent variables. 

These methods of collecting data are all relatively insensitive to one 
another in that a specific error in one measurement is very unlikely 
to affect another measurement. Thus, the methods can be used to 
corroborate each other. 



* The Bell System as a common carrier is entitled to certain privileges to monitor 
the quality of its services. Bell Laboratories as an agent of the Bell System is extended 
these privileges. Only data necessary to ensure good service are gathered, and they are 
kept secure, in strict confidence, and statistically anonymous. To guarantee customer 
privacy, data are never gathered after a call is placed, i.e., after called party answers. 

FIELD TESTING TELEPHONE SERVICES 1597 



3.3.2 Analytic tools and techniques 

The practice of feeding back the results as input to the experimental 
design process, while providing an efficient data gathering technique, 
places an additional burden on analysis. Results must be provided in 
a timely manner to be of use in formulating the next service improve- 
ments to be tested. Figure 4 illustrates a data processing stream used 
to field test the Calling Card Service. 

Standard statistical routines must be used with caution since the 
assumptions on which they are based may be violated. For example, 
sampling is often nonrandom. 

One heuristic is to leave the service unperturbed for some reasonable 
period of time (two or more weeks depending on the call volume). The 
extent of variations or noise in the data is measured and later used as 
a benchmark to assess meaningful variations potentially due to service 
manipulations. 

3.3.3 Test service provisioning 

A system to deliver a voice-prompted test service should include the 
ability to deliver tones and announcements, to route to an operator, 
and to receive dialed digits. Connection to the network, billing, and 
data processing and storage also need to be considered. 

3.3.4 Acquire and prepare sample 

Obtaining sufficient numbers of representative customers for the 
field test is important. The field test approach usually requires thou- 



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Fig. 4 — Data processing stream. 
1598 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



sands of calls to provide adequate data. Inability to obtain sufficient 
customers, if not attributable to test limitations alone, may be a key 
indicator of the potential failure of a new service. The means for 
selecting and acquiring customers has to be designed with test validity 
in mind. 

The process of obtaining participants and assigning them to groups 
can be the source of some of the strongest rival hypotheses. Random 
selection is the principal counteraction to ensure the representative- 
ness of the population sample and group equivalence. But, randomi- 
zation is not always possible. Moreover, even when it can be used, 
aspects of the customer acquisition and assignment process can still 
introduce biases that will limit the ability to generalize. 

Selection processes are outlined below: 

1. Determine target population using interviews and market studies. 

2. Characterize the history, predisposition, environmental influ- 
ences, etc., of target population. 

3. Draw customers randomly from within the target population and 
from a similar group outside the target population. Sampling cus- 
tomers outside the target population will help to validate the use of 
the target groups for tests. If random selection is not possible, select 
customers who are matched to characterization of the target popula- 
tion. 

4. Solicit participation for the test in a representative way. Prefer- 
ably, contact customers in the same way they would be contacted for 
the final service. 

5. Check participants for degree of similarity to target population 
characterization. 

6. Interview random samples of those who agree and disagree to 
participate to determine the reasons for participation or nonpartici- 
pation. For example, the fact that it is a test rather than an actual 
service may have influenced either decision. Also, use a priori factors 
to account for any differences between those who agreed and those 
who refused. 

7. Randomly assign participants to control groups and treatment 
groups. If random assignment is not possible, use self-selection of 
treatments. 

8. Use measurements taken before the test to help determine the 
nature of group differences. 

3.3.5 Results utilization 

One of the largest pitfalls in the practice of implementing an 
evaluation of telephone service can be the lack of assurances and 
mechanisms for integrating evaluation results into the final product. 
Results from the test must be timed to allow development of changes 

FIELD TESTING TELEPHONE SERVICES 1599 



in the final product. A responsible organization must be named for 
coordinating the integration of results and the final product itself 
must be designed to allow changes. Appropriate flexibility in the initial 
design of the product can reduce delays in product introduction. 

IV. DESIGNING TO COUNTERACT OTHER EXPLANATIONS 

Steps taken in designing the test — which decrease confidence in 
rival hypotheses and increase confidence in the working hypotheses 
(the one we wish to prove) — are called counteractions. In laboratory 
research, some typical counteractions are: 

• Orthogonality and counterbalancing of independent variables 

• Control and preclusion of extraneous variables 

• Random collection of subjects in the attempt to eliminate selection 
bias. 

Field settings require adapting such measures to real-world con- 
straints. 

The counteractions useful in field tests can be divided into those 
required for evaluating a static service (i.e., determining if a service 
meets a priori acceptability standards) and those required for evalu- 
ating attempts to improve a service. Counteractions can be adapted to 
preclude, disconfirm, or control rival hypotheses. 

4. 1 Service evaluation 

One of the simplest counteractions is to take multiple measurements 
of the same service, such as measurements of usage, satisfaction, and 
performance. Taking these measurements in more than one way 
(multiple methods) is also useful. Confidence in a particular result is 
increased if different sources point to the same conclusion. 

One fear (rival hypothesis) that occasionally strikes is that the data 
are somehow mutilated to spuriously inflate results. This fear became 
real in the Calling Card Service field trial when the service began 
performing better than expected. Interviews, observation, and billing 
data corroborated the computer-collected data so strongly as to explode 
this rival hypothesis. Test calls removed any remaining shards of 
doubt. 

Many rival hypotheses are based on test time. For example, the 
results may be due to some unusual circumstance or event, or the test 
may give rise to a trend in usage or performance that may be transitory 
(e.g., novelty effects or start-up effects) or the test may give rise to 
cyclic or delayed effects. One simple counteraction used in the Calling 
Card Service field trial to account for these problems was to repeat a 
test or take continued measurement of the service over time. If a 
unique circumstantial or historical event affected the outcome of a 

1600 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 






test, then subsequent measures could provide evidence to support or 
negate this rival hypothesis. 

Before, during, and after usage measurements of all coin stations 
(trial and nontrial) at the airport were inspected to determine if any 
events, trends, or cyclic phenomena confounded the data. Specifically, 
the Christmas holiday season and an airline strike had to be taken 
into account. 

While multiple measurements and time-spaced testing counteract 
many problems, they give rise to problems of their own. One measure- 
ment may affect another. For example, repeated interviewing may 
cause customers to change their behavior more as a function of the 
interviewing process than the service itself. 6 Fortunately, the bulk of 
the measurements typically taken in a telephone service field trial are 
made on-line and are unknown to the telephone caller.* The customer 
is not usually aware in these tests that digits dialed, on-hooks and off- 
hooks are recorded and time stamped. These measures are presumably 
nonreactive, and thus there is no plausible explanation of measure- 
ment affecting customer behavior and attitude. 

One could avoid the problem of reactivity by using only nonreactive 
measures. But interviews and questionnaires provide invaluable data. 
We handled this problem in the Calling Card Service field trial by 
interviewing some customers once, others twice, and still others not 
at all. Comparisons of these groups in terms of nonreactive measures 
and subsequent interviews, however, did not substantiate a reactivity 
effect. 

Establishing a control group is another strategy that can be used to 
help determine if the results were due to historical events or arbitrary 
circumstances. The assumption is that those extraneous events or 
circumstances that affect the treatment group also affect the control 
group. To the extent that the precision of the measures allow, differ- 
ences between the control group and the treatment group can, there- 
fore, be attributed to the presence of the treatment, that is, the service. 

People at nontrial coin stations at the airport were interviewed as a 
control for interviews taken at trial coin stations. This procedure 
allowed us to determine if there were any changes in customer attitudes 
that might have been attributable to events alone and not to service. 
The interview control group thus served as a counteraction to the rival 
hypothesis of history. For example, those people interviewed some 
days were angry because of plane delays. If this irritation had an 
effect, it would show up in both treatment and control group scores. 



* The customer generally is aware that a test is being conducted and that service is 
being measured; thus, the problem of test reactivity cannot be completely discounted. 

FIELD TESTING TELEPHONE SERVICES 1601 



Randomization in the selection process assures equivalence between 
the treatment and control groups. If randomization is not possible, a 
plausible rival hypothesis is that the people assigned to one group 
differ, on the average, from those in the others and that these intrinsic 
differences are the real cause of any observed difference among the 
groups. A method for determining whether such rival hypotheses are 
correct is to make measurements of the groups before the treatment 
(service) is administered. Comparing the pretreatment and post-treat- 
ment observations of the group given the trial service with simulta- 
neous observations of the control group (not given the trial service) 
tests the rival hypotheses that these two groups are inherently differ- 
ent, or in other words, that results are due to the history of the 
customers or their maturation or learning during testing. 

Customers were interviewed and billing data were tracked before 
and after the Calling Card Service field trial. These data were used to 
determine the differences among customers and between trial and 
nontrial stations. 

4.2 Improving service 

In the preceding discussion, counteractions for a static service 
evaluation were discussed. A new service can be said to consist of a 
set of variables that may be manipulated to possibly improve service. 

The key question is: How can we be sure that changes in service 
outcome are due to our service manipulations? Establishing causal 
connections for what improves or degrades service increases under- 
standing. Increased understanding will tend to increase confidence in 
predictions of how the final service will fare. 

4.2. 1 Varying the service 

A simple model of service variation is depicted in Fig. 5. The knobs 
in the figure represent the independent variables; the meters, the 
dependent variables. The object of varying the service is to manipulate 
the knobs in such a way as to cause the meters to register a beneficial 
change in service. If the meters are considered to show customer 
satisfaction, usage, and performance, the object then is to find the 
combination of knob positions that maximizes the readings on each 
meter (metaphorically speaking). 

With every knob manipulation, knowledge and understanding is 
increased, whether the meters change positively, negatively, or not at 
all. Knowledge gained from the previous adjustment permits efficient 
and effective design of subsequent service adjustments. However, such 
a test-adjust-test method requires a system that can provide very quick 
analysis of results. 

1602 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 




ANNOUNCEMENTS 



o 



PERFORMANCE 



SATISFACTION 





ERROR HANDLING 



o o 



O "INDEPENDENT VARIABLE ^ = DEPENDENT VARIABLE Zj = ith PROTOCOL 

Fig. 5— Field trial metaphor— with results fed back as input into the field trial design. 

4.2.2 Increasing confidence in service manipulations 

Improving service can be thought of as repetitions of static service 
evaluation. The same counteractions discussed earlier can be used and 
augmented for service improvement. To account for the possibility of 
other events interposing effects on the dependent variables coincident 
with the adjustment of a service, the concept of the control group is 
again appropriate. 

One new problem that is introduced in improving service is that 
multiple treatments (changes) may interact with each other. That is 
to say, customers' responses to a subsequent service may not be the 
same as those to the first service they experienced. Further, the very 
act of changing the service may impact attitudes and customer per- 
formance. 

Adding a new group of customers for every new protocol iteration 
counteracts this threat to validity. (Appendix A contains notations for 
representing this design consideration and the others discussed here.) 

The rudiments of these design principles were used in the Calling 
Card Service field trial. Service was manipulated in the trial in an 
attempt to improve service. A particular service configuration is here 
called a service protocol. Because many of the trial phones were in the 
airport, there were always a great number of new customers trying the 
service, more than enough to support the manipulations. 



FIELD TESTING TELEPHONE SERVICES 1603 



When customers dialed 0+NPA NXX XXXX at trial stations a 
tone prompt was given (sometimes followed by an announcement 
prompt) and the following things (in most protocols) could happen: 

1. The customer could dial a credit card number. 

2. The customer could time out without dialing and be connected to 
an operator. 

3. The customer could dial after the prompt and be connected to 
an operator. 

4. The customer could abandon the call. 

Ideally, all customers with credit card numbers would dial them. All 
others would dial after the tone prompt to reach an operator. 
Practically speaking, this was not possible. Rather, different protocols 
were tested to attempt to increase the proportion of dialed credit card 
calls, increase the proportion of customers who needed an operator to 
dial 0, or decrease abandons. 

Figure 6 summarizes the service manipulations for the placarded 
coin stations. Figure 7 shows the proportion of the four classes of call 
dispositions: (1) dial credit cards, (2) dial 0, (3) abandons, and (4) 
time-outs for each protocol for the placarded coin stations. The area 
under each curve represents the incremental proportion of 0+ calls. 

While these curves are revealing, they cannot be used alone to 
determine the best protocol, i.e., the one with the highest satisfaction, 
performance, and usage. However, unacceptable protocols can readily 
be identified: they are those with abandonment rates in excess of 25 
percent and those with dialed credit card call rates less than 25 percent. 

Fortunately, the first coin placarded service protocol had low aban- 
donment rates and high credit card dialing rates. The subsequent 



MAJOR COMPONENT 
TESTED 


1 2 3 


4 5 6 


COIN STATION PROTOCOL 

7 8 9 10 11121314151617 18192021222324 


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PROMPT 
ANNOUNCEMENT 

SECOND PROMPT 
ANNOUNCEMENT 

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1604 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



100 




9 12 

PROTOCOL 

NOTE: PROTOCOLS WITHOUT A TONE-ONLY INDICATOR HAVE A TONE AND AN ANNOUNCEMENT. 
PROTOCOL 17 INCLUDES A SPECIAL ANNOUNCEMENT DESIGNED TO DISCOURAGE CALLS 
FROM UNENABLED ROTARY STATIONS. 

NOTE: THESE CURVES REPRESENT INCREMENTAL PERCENTAGES. 

Fig. 7— Dialing performance at placarded coin stations by protocol. 

manipulations were primarily aimed at improving service, although 
clearly the opposite effect was sometimes achieved. 

A changing volume of 0+ calls and a changing call mix were plausible 
explanations for one service protocol doing marginally better than 
another. As Figure 8 shows this was sometimes a consideration. 

Another rival hypothesis was related to assumptions about those 
who abandoned. If all or a large number of those who abandoned were 
credit card customers, estimates of the proportion of credit card dialers 
could vary significantly. Figure 9 shows the percentage of dialed credit 
card calls (of all credit card calls) with and without abandons counted 
as credit card calls. Including and excluding abandons in this way 
provides lower and upper bounds, respectively, of the percent of credit 
card calls dialed. 

Still another rival hypothesis was that usage (or attempts) may be 
higher, but performance lower when comparing one protocol to an- 
other. Figure 10 illustrates success rates by protocol. 

Rival hypotheses due to repeated usage (familiarity and learning) 
were accounted for by sorting out and examining results from repeat 

users. 

Service protocols were compared to determine the effect of a partic- 
ular manipulation. Figures 11 and 12 compare two protocols in terms 
of abandonments and percent of 0+ dialing. These figures lead to the 
conclusion that repeating a prompt announcement in this service does 
not increase dialing but does increase abandons. Thus, repeating 
announcements is a less desirable alternative. 

FIELD TESTING TELEPHONE SERVICES 1605 



+ TRAFFIC 




NOTE: PROTOCOLS WITHOUT A TONE-ONLY INDICATOR HAVE A TONE AND AN ANNOUNCEMENT. 
PROTOCAL 17 INCLUDES A SPECIAL ANNOUNCEMENT DESIGNED TO DISCOURAGE CALLS 
FROM UNENABLED ROTARY STATIONS. 

Fig. 8 — Volume of 0+ traffic at placarded coin stations. 



< 

o 

tw 

LU O 

If 

"< 

Ql- 

LU f 

II 
o< 

UJ 05 

o J 

<^ 

I- < 



100 



80 



60 



40 



20 



WITHOUT 
ABANDONMENTS 




A= TONE ONLY 

^V-A— ' L 



-&- 



J-A >-*■ 



NOTE: PROTOCOLS 12, 13, 15 AND 16 MANIPULA- 
TIONS INVOLVED LIMITING OPERATOR 
ACCESS WHICH REDUCES VOLUME 
AND CAUSED + CUSTOMERS TO EITHER 
ABANDON OR DIAL A CREDIT CARD 
NUMBER. 



' A 

12 15 18 21 24 

NOTE: PROTOCOLS WITHOUT A TONE-ONLY 
INDICATOR HAVE A TONE AND AN AN- 
NOUNCEMENT. PROTOCOL 17 INCLUDES 
A SPECIAL ANNOUNCEMENT DESIGNED 
TO DISCOURAGE CALLS FROM UNEN- 
ABLED ROTARY STATIONS. 



Fig. 9— Dialed credit card calls with and without abandonments by protocol. 



4.2.3 Comparison groups 

There are two ways of making service comparisons in the test design 
just discussed, which consisted of staggered subjects and measure- 
ments of responses to service refinements. First, customer comparisons 
can be made across service changes. This consists of multiple meas- 
urements or time-spaced measurements of the same customer. The 



1606 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



100 




70 



1 
1/1 



80 



3 4 
2/1 



J I L 

5 6 7 8 

3/1 



J L 



J I L 



10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 

4/1 5/1 6/1 

PROTOCOL VARIATION 
DATE (1978) 



Fig. 10 — Customer dialing success rate. 




OPERATOR ACCESS 



ANNOUNCEMENTS: 

"PLEASE DIAL YOUR CARD NUMBER OR 
(ANOTHER) ZERO FOR AN OPERATOR" 



ANNOUNCEMENT 2 
/ 
/ 

L 



15 
SECONDS 



30 



35 



Fig. 11 — Abandonments as a function of repeated announcements at coin placarded 
stations. 

error variance is small because there are no intersubject differences, 
but there is multiple treatment interference. Second, service compar- 
isons can be made across new subject groups, but treatment effects 
are confounded with history and by any bias introduced by the selec- 
tion of groups. 

Comparison groups can be arranged to preclude history as a con- 



FIELD TESTING TELEPHONE SERVICES 1607 



80 






TONE AND 1 
ANNOUNCEMENT 


TONE AND 2 
ANNOUNCEMENTS 


60 

< 

+ 
o 
u. 

2 « 








• 


3 

Z 






— — OPERATOR ACCESS 












o 

DC 

S 20 




ANNOUNCEMENTS: "PLEASE DIAL YOUR CARD NUMBER 
OR (ANOTHER) ZERO FOR AN 
OPERATOR." 




/ ANNOUNCEMENT 1 


ANNOUNCEMENT 2 






/ / 






I 



5 10 15 20 26 30 

^ SECONDS 

TONE 

Fig. 12— Dialing as a function of repeated announcements at coin placarded stations. 

founding variable by offering different service arrangements simulta- 
neously (at different telephones, for example). For best results, each 
of these comparison groups should be as similar as possible except for 
any planned differences in treatment (service). 

In the Calling Card Service field trial, we devised three comparison 
groups: noncoin stations, placarded coin stations (with special bright 
orange instruction cards), and placardless coin stations. These com- 
parison groups were not mutually exclusive. Crossovers occurred, 
especially between placarded coin and placardless coin groups. But for 
every comparison group, and, as discussed, for every manipulation, 
there were new customers. Service changes were replicated across 
these comparison groups further increasing confidence and providing 
information about the effects of the station type. 

4.2.4 Refinement 

Because the number of variables and variable states in a field test 
of this kind is usually large, only a small subset of the number of 
possible treatment combinations can be used. Moreover, the protocol 
is evolving and a delay is often necessary in the testing of different 
combinations. Unfortunately, this delay means the manipulation is 
confounded with the history of the customer population. However, 
prudent selection of changes and repetitions within a treatment group 
and across comparison groups can yield a more complete understand- 
ing of the effects of the service components and their interactions. 

1608 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



In the Calling Card Service, the primary objective of the service 
manipulations was to make reasonable changes which were hypothe- 
sized to increase usage, satisfaction, and performance. This objective 
was sometimes subjugated to the purpose of increasing confidence in 
the belief that the changes in the independent variables (and not the 
parameters) caused the observed changes in the dependent variables. 
One such manipulation was to deliberately make it progressively more 
difficult for the customer to get to an operator, i.e., protocols 12, 13, 
15, and 16. It was hypothesized that more customers would use their 
credit card if it were made relatively more difficult to obtain an 
operator. However, this hypothesis was not borne out; the proportion 
of credit card calls dialed was either unchanging or decreasing, and 
abandons increased as one would suspect. Clearly, other manipulations 
were more successful. 

As the treatment change chart shows, changes in the state of more 
than one independent variable were made more often than not. The 
large number of variables prohibited single sequential changes in each 
variable. For example, the error-leg protocol was manipulated inde- 
pendently and simultaneously with the access-leg protocol many times. 
Evidence gathered from protocols prior to this practice showed little 
or no interaction from changes in the access leg and the error leg, 
except that the number of people making errors fluctuates. 

Inferences made about the protocol change were made in terms of 
the multiple change because the independent variables were con- 
founded. Inferences based on effect separation and independence 
assumptions were made cautiously and verified, when possible, in later 
manipulations. 

4.2.5 Replication 

Any changes in the dependent variables caused by a change in the 
protocol (or service) and not by history should be present in successive 
identical tests (within the bounds of measurement error). Replication 
of effects increases confidence in the hypothesis that a change in 
protocol actually causes a change in the dependent variable being 
measured. As a practical matter, the utility of repeated replications of 
a single treatment is sharply reduced by the need to manipulate as 
many variables as possible in the time allowed. However, intermittent 
replications can serve to benchmark drifting or trending data. 

On several occasions, we repeated protocols within and across com- 
parison groups in the Calling Card Service field trial. Replications 
afforded an increase in confidence by allowing an assessment of 
changes in dependent variables due to confounding of external and 
internal parameters with the independent variables. The replications, 
in effect, provided a basis for comparison. And the replications in- 

FIELD TESTING TELEPHONE SERVICES 1609 



creased confidence in the assertion that the observed changes in the 
dependent variable were caused by the deliberate change in the inde- 
pendent variables. For example, protocol 14 amidst protocols 12, 13, 
15, and 16 (coin placarded stations) was a replication of an earlier 
protocol and supported the hypothesis that the poor performance of 
the other protocols was real and not an artifact of internal or external 

conditions. 

Some replications were designed to provide more information about 
the contributing effects of certain service components. Most notably, 
major service changes were tested with both the tone-only and tone- 
and-announcement conditions. For example, protocol 13 (coin placard 
station) was the same as protocol 12, but without the prompt an- 
nouncement. This is similarly true for protocols 15 and 16. 

4.2.6 Partial counterbalancing 

Arranging the treatment order in special ways— e.g., the Latin 
Square design — across comparison groups provides for pairwise com- 
parisons of different treatment orderings. Such arrangements, how- 
ever, are often not practical in field trials of telephone services because 
of the large number of variables and variable states (treatment con- 
ditions) that should be tested. The large number of treatment combi- 
nations required of typical counterbalancing techniques preclude their 
use. Manipulation of protocols on the basis of data gathered from prior 
manipulations also precludes planned counterbalancing. 

But it may be possible partially to counterbalance treatment pairs 
across comparison groups in order to assess some multiple treatment 
order effects. If the manipulations evolve, the application of counter- 
balancing schemes have to be delayed by at least one time frame to 
have knowledge of the treatment pair. 

4.2.7 Post-manipulation static study 

After service manipulations are finished, it is useful to study the 
final service at rest. In this period in the Calling Card Service field 
trial (protocol 24), transient effects due to changes in the service were 
not present, thus improving predictions of the final service. 

V. CONCLUSION 

Many service issues were resolved by the trial of Calling Card 
Service. Most important, the customers who tried the service contin- 
ued to use it because they felt it was faster and more convenient than 
operator-assisted credit card calling. Moreover, the design of the 
service was critically dependent on the results of the field trial manip- 
ulations. Both announcements and instruction placards were found to 
be very effective in stimulating customers to dial. The field trial data 

1610 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



provided objective measurements of optimum customer usage and 
acceptance and lower rates of error and abandonment in the service 
offered. Table I lists the criteria found most useful in selecting the 
attributes of the final service. 

When Calling Card Service was first offered in Buffalo in July 1980, 
a product follow-up evaluation study was conducted to monitor cus- 
tomer use, performance, and acceptance levels. The measurements of 
actual service conformed closely to estimates made from field trial 
data and, thus, support the utility of test methodology in guiding 
service design choices. The methodology developed for evaluating 
Calling Card Service is now being applied to the next generation of 
services, such as teleconferencing. 

VI. METHODOLOGY SUMMARY 

The pre-field trial activities of analysis, interviews, and laboratory 
studies are undertaken to refine the service definition and assess the 
potential of its success. A study plan is constructed which defines 
objectives, resources and constraints, study variables, acceptance cri- 
teria, and study design. Field test requirements are developed that 
specify the data collection, analysis, and customer acquisition and 
preparation procedures as well as specify the hardware, software, and 
network aspects of a telephone service test vehicle. 

Given adequate requirements the test is developed and implemented. 
During the test, the service is manipulated and data are collected and 
analyzed to optimize criteria of usage, performance, and satisfaction. 
Trade-offs are made relative to available resources, data validity, 
confidence in results, and time constraints. If success is predicted for 
the service being tested, results are then integrated into the design 
and the service is offered and monitored. Figure 13 summarizes the 
total process of conducting a field test of a telephone service. 

Table I — Criteria for selecting service attributes 

Independent Variables Dependent Variables 

1. Announcement Presence a. Percentage Dialed 

b. Abandons 

2. Announcement Wording a. Percentage Dialed 

b. Confusion (interviews) 

c. Abandons 

3. Number of Attempts Allowed a. Success Rate 

b. Percentage of Subsequent Attempts 

4. Operator Access a. Percentage Dialed 

b. Abandons 

c. Satisfaction (interviews) 

5. Interevent Timing a. Distribution of Times to First Digit 

6. Interdigit Timing a. Distribution of Pauses Between Digits 

7. Protocol (service in general) a. Percentage Dialed 

b. Satisfaction (interviews) 

c. Success Rate 

8. Delays a. Abandons 



FIELD TESTING TELEPHONE SERVICES 1611 







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1612 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



VII. ACKNOWLEDGMENTS 

I would like to thank E. C. T. Walker and C. A. Riley for their 
valuable comments on this manuscript. K. R. Hickey, R. J. Jaeger, N. 
S. Pearson, and J. L. Santee are thanked for their input as well. The 
Calling Card Service test depended heavily on the contributions of T. 
M. Bauer and E. A. Youngs. 

REFERENCES 

1. M. R. Allyn, T. M. Bauer, and D. J. Eigen, "Planning for People: Human Factors 

in the Design of a New Service," Bell Lab. Rec, 58, No. 5 (May 1980), pp. 55- 
161. „ , 

2. D. J. Eigen and E. A. Youngs, "Calling Card Service— Human Factors Studies, 

B.S.T.J., 61, No. 7 (September 1982), pp. 1715-35. 

3. D. T. Campbell and J. C. Stanley, Experimental and Quasi-Experimental Design for 

Research, Chicago: Rand McNally, 1966. 

4. D. T. Cook and D. T. Campbell, Quasi- Experimentation Design and Analysis Issues 

for Field Settings, Chicago: Rand McNally, 1979. 

5. H. M. Parsons, Man-Machine System Experiments, Baltimore: Johns Hopkins, 

1972. 

6. E. J. Webb et al., Unobtrusive Measures: Nonreactiue Research in the Social Sciences, 

Chicago: Rand McNally, 1966. 



APPENDIX A 

Field Evaluation Design Notation 

To provide another perspective on the field design methods, the 
following notation is provided. 

A.I Service 

A service (or treatment) can be defined by set of dependent variables 
with specific values, represented here as a vector Z. 

Z\ 

z = 



A.2 Measurements 

Let stand for observation. A matrix of n kinds of measurement 
taken in m different ways is represented by 6. 



= 



On O12 ••• Oi, 



B i n2 ••• r 



FIELD TESTING TELEPHONE SERVICES 1613 



When multiple measures (taken multiple ways) are repeated, the 
notation is: 

(T = 61 ■ • ■ m • 

A.3 Improving service 

Two aspects of the field study, static service evaluation and improv- 
ing service, could be represented as:* 

Static Service Evaluation Improving Service 



oy z or Zx 



6? ... 6? t n 6KV1 



This design effectively constitutes repetitions of the static service 
evaluation. 



A.4 Control group 



A'Oq Zq a®? Z\ a®2 • * " A^n Z n A®n+\ 



Treatment 
Group 



A 'OS" A'Wl A'O™ ■ • • A '0« A'On+1 



Control 
Group 



A.S Staggered treatment groups 

New subjects are added (or are available) at each treatment change. 
Limited resources usually necessitate the continued manipulation of 
the variables within treatment groups. The line offsets the control 
group from the treatment groups and denotes unequivalence of the 
groups. 

Treatment 
Group 1 

Treatment 
Group 2 



A '0]io Zq a 'On Z\ a0?2 • • • aOiJ, Z n A^Tn+l 

A'V2\ Z\ a^TI • • • A^tn Z n A^2n+l 



l'Onn Z n AVnn+1 



Treatment 
Group n 



vO 



A-Vn+iQ 



i-O; 



A'Vn+n 



A'On+12 



AVn+ln+l 



Control 
Group 



* %i denotes the vector of service-independent values for the ith service change 
(treatment). A 0" denotes the matrix of multiple measurements by multiple methods 
measured m times for the itb service (treatment) change. The left-hand A ' subscript 
(versus A subscript) denotes that some measurements present in the trial may not be 
available in the pretrial measures (or in the control group). 



1614 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983 



To reduce the notational burden, let o>, denote the ith staggered 
treatment group. 



COfl 



A'Oo i4'0i" A'O? • • • A'0n+1 



A.6 Staggered treatment groups with comparison groups 

o>io 



d>12 



Comparison 
Group 1 



wi,, 



co 2 o 

W21 

^22 



Comparison 
Group 2 



U2n 



U„2 



Comparison 
Group n 



OJn 



B ••■ C ... c 

Note that the Control Group. C, is augmented with historical and 
follow-up measurements. 

HELD TESTING TELEPHONE SERVICES 1615 



A.7 Replications 

Replications are denoted by the appropriate repetition of protocol 
time frame subscripts on the independent variable vector: 



aW z A-b? Z, A 0? Z q aOT Z 2 aO? •■ Z n A 0\ 



A.8 Partial counterbalancing 



I'Oioi Zq ^Oiil Zy 



a'OSi Z\ 



O121 Zi 
/1O221 Z 2 

A'0z2l Zi 



l'0l02 Zq A'0ll2 Z\ ^0i22 Zq 



I'Ojjta Z\ a0222 Zq 



1-0322 Zq 



Comparison 
Group 1 

Comparison 
Group 2 



The two boxed groups are the time-delayed counterbalanced treatment 
pairs Zq and Z\. 



AUTHOR 

Daryl J. Eigen, B.A. (Psychology), 1972, M.S. (Electrical Engineering), 
1973, University of Wisconsin; Ph.D. (Industrial Engineering), 1981, North- 
western University; Bell Laboratories, 1973—. Mr. Eigen initially worked in 
the Human Performance Technology Center. He then was involved in feature 
and service planning for the Traffic Service Position System and, later, the 
No. 4 ESS. He is currently Supervisor of the System Analysis and Human 
Factors Group for No. 4 ESS. Member, IEEE, APA, Human Factors Society, 
and Tau Beta Pi. 



1616 THE BELL SYSTEM TECHNICAL JOURNAL, JULY-AUGUST 1983